# DBMS History ## 1950s and early 1960s * Data processing was using magnetic tapes for storage. However, tapes provide only sequential access * Punched cards were used for input ## Late 1960s and 1970s * Hard disks started being used and they allowed direct access to data * Network and hierarchical data models were in widespread use * Edward Codd defined the relational data model and later won the ACM Turing Award for this work * IBM Research begun the System R prototype and UC Berkeley begun Ingres prototype * High-performance transaction processing was introduced ## 1980s * Research relational prototypes evolved into commercial systems * SQL became industrial standard * Parallel and distributed database systems were used * Object-oriented database systems were introduced ## 1990s * Large decision support and data-mining applications were developed along with large multi-terabyte data warehouses * The emergence of web commerce and web search engines led to the development of data storage structures and database systems to support web search data ## Early 2000s * XML and XQuery became standards * Automated database administration was introduced ## Late 2000s * Giant data storage systems were introduced, such as BigTable (Google), Hbase (Apache), PNuts (Yahoo!), Dynamo (Amazon), Cassandra (Facebook), Voldemort (LinkedIn) * Distributed processing frameworks like MapReduce (Hadoop), Pig (Yahoo!), Dryad (MSFT), etc were introduced --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://vikram-bajaj.gitbook.io/cs-gy-6083-principles-of-database-systems/main-1/dbms-history.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.